This project delves into the analysis of over 11,000 Zomato delivery records to uncover patterns influencing delivery efficiency. By examining variables such as product weight and shipment mode, we aim to provide actionable insights to enhance operational performance.
- Analyze Delivery Patterns: Identify factors affecting delivery times and success rates.
- Optimize Operations: Recommend strategies to improve delivery efficiency.
- Enhance Customer Satisfaction: Understand variables that influence customer experience.
- Data Analysis: Microsoft Excel (Pivot Tables, Charts)
- Data Visualization: Excel Charts, 100% Stacked Column Charts with Percentage Labels
- Lightweight Products: Deliver faster compared to heavier items.
- Air Shipment Mode: Shows better delivery rates than other modes.
- Delivery Time Trends: Identified peak hours and bottlenecks.
- Weather Impact: Analyzed how different weather conditions affect delivery times.
The analysis includes various visualizations to represent the data effectively:
- Pivot Charts: Summarize key metrics and trends.
- 100% Stacked Column Charts: Show distribution of delivery times across different categories.
| File Name | Description |
|---|---|
README.md |
Project overview and documentation |
Zomato_dashboard.xlsx |
Excel file containing analysis and visualizations |
- Integrate machine learning models to predict delivery times.
- Expand analysis to include customer reviews and ratings.
- Develop an interactive dashboard for real-time insights.
For feedback or inquiries, please reach out to Divyesh.
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